An important current goal in molecular biophysics is to determine the extent to which protein behavior observed in vitro is reflective of that occurring in vivo. Experimental approaches based on in-cell NMR and fluorescence techniques are beginning to bridge the gaps in knowledge, but such studies can present significant technical challenges in terms of execution, resolution and interpretation; in addition, they typically allow only one or a few types of macromolecule to be studied at a time. To provide a complement to these experimental approaches, the purpose of this proposal is to develop a Brownian dynamics (BD) simulation method capable of modeling intracellular environments at a near-atomic level of resolution, and to apply the method to simulate key aspects of protein behavior in a model of the cytoplasm of the prokaryote Escherichia coli. The simulation method will allow all macromolecules to be treated as fully flexible, thereby allowing protein folding events in vivo to be modeled, and will provide a rigorous modeling of the hydrodynamic interactions that are crucial to include if the diffusional properties of macromolecules are to be accurately captured. Three Specific Aims will be pursued. In Aim 1, a comprehensive, parallelized coarse-grained (CG) BD simulation method will be completed that allows large-scale biomolecular systems to be modeled. The proposed work will involve (a) the implementation of a novel method for modeling hydrodynamic interactions on a very large scale, and (b) parallelization of the simulation code so that it runs efficiently on common distributed-memory computer clusters. In Aim 2, a comprehensive force field for use in CG simulations of protein/RNA systems will be derived for use with the simulation code developed in Aim 1. Importantly, parameterization of the force field will be performed in two fundamentally different ways: 'top down', using experimental data on the thermodynamics of weak macromolecular interactions, and 'bottom up', using all-atom, explicit-solvent molecular dynamics simulation data. In addition to being parameterized in a comprehensive way, the derived CG force field will be unique in also having its hydrodynamic parameters explicitly parameterized. Finally, in Aim 3, the methods developed in Aims 1 and 2 will be used to perform a series of simulation studies examining fundamental aspects of protein behavior in the highly crowded conditions encountered in vivo. BD simulations of protein folding thermodynamics in concentrated single-protein solutions will be compared with the results of H/D exchange measurements. BD simulations of protein diffusion in a model of the cytoplasm of E. coli will be aimed at reproducing in silico the results of 'in-cel' NMR and fluorescence-recovery-after-photobleaching (FRAP) experiments, also performed in E. coli. Finally, BD simulations of the thermodynamics and kinetics of protein folding in the E. coli cytoplasm will also be carried out and compared with corresponding experimental data. If successful, the methods developed and applied here will provide a fundamentally new view of macromolecular behavior in vivo that will be capable of rationalizing previously poorly understood experimental results and making directly testable predictions. Both the simulation code and its attendant force fields will be made freely available to the community.